Process / pipelineBioinformatics / omics

Multi-omics Gene Set Enrichment Analysis

Multi-omics gene set enrichment analysis (multi-omics GSEA) is a computational pipeline that applies GSEA logic simultaneously across two or more molecular measurement layers — such as transcriptomics, proteomics, and metabolomics — to identify biological pathways or gene sets that are coordinately dysregulated across omics platforms. By integrating ranked molecular signatures from each layer, it reveals pathway-level convergence that no single omics platform could detect alone.

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Sources

  1. Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., & Mesirov, J. P. (2005). Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences, 102(43), 15545–15550. DOI: 10.1073/pnas.0506580102
  2. Meng, C., Zeleznik, O. A., Thallinger, G. G., Kuster, B., Gholami, A. M., & Culhane, A. C. (2016). Dimension reduction techniques for the integrative analysis of multi-omics data. Briefings in Bioinformatics, 17(4), 628–641. DOI: 10.1093/bib/bbv108

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Referenced by

ScholarGateMulti-omics gene set enrichment analysis (Multi-Omics Gene Set Enrichment Analysis). Retrieved 2026-06-04 from https://scholargate.app/en/bioinformatics/multi-omics-gene-set-enrichment-analysis